Brian O'Connor  UBCO Psychology  UBCO 
A First Steps Guide To The Transition From Null Hypothesis Significance Testing To More Accurate And Informative Bayesian Analyses
Reference:
O'Connor, B. P. (2017). A first steps guide to the transition from null hypothesis significance testing to more accurate and informative Bayesian analyses. Canadian Journal of Behavioral Science, 49(3), 166182. http://dx.doi.org/10.1037/cbs0000077
Abstract:
This article begins with a brief summary of the problems with null hypothesis significance testing (NHST), followed by a short, nontechnical description of perhaps the most useful NHST alternative, Bayesian methods. Simple R commands and output for Bayesian correlations, regressions, and ANOVA are provided. This is followed by examples of how to describe Bayesian analyses in the Methods and Results sections of articles. The focus is on taking the cautious first steps in a transition away from NHST.
Click here for the R code and output for the Bayesian data analyses that were described in the above article:
The links below provide R code and output for Bayesian analyses of the example datasets that are used in the following textbook:
Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using R. Los Angeles, CA: Sage.
The R code below was produced in collaboration with Dylan Ermacora.
Chapter 
R code 
R output 

Chapter 6: Correlation 
Ch6_Correlation.R  Ch6_Correlation.txt 

Chapter 7: Regression 
Ch7_Regression.R  Ch7_Regression.txt 

Chapter 8: Logistic Regression 
Ch8_Logistic.R  Ch8_Logistic.txt 

Chapter 9: Comparing two means 
Ch9_Two_Means.R  Ch9_Two_Means.txt 

Chapter 10: Comparing several means (ANOVA) 
Ch10_ANOVA.R  Ch10_ANOVA.txt 

Chapter 11: Analysis of covariance 
Ch11_ANCOVA.R  Ch11_ANCOVA.txt 

Chapter 12: Factorial ANOVA 
Ch12_Factorial_ANOVA.R  Ch12_Factorial_ANOVA.txt 
Brian P. O'Connor
Department of Psychology
University of British Columbia  Okanagan
Kelowna, British Columbia, Canada
brian.oconnor@ubc.ca